similar to: plotting zoo using datetime as xlim

Displaying 20 results from an estimated 600 matches similar to: "plotting zoo using datetime as xlim"

2013 Aug 26
2
Partial correlation test
Dear all, I'm writing my manuscript to publish after analysis my final data with ANOVA, ANCOVA, MANCOVA. In a section of my result, I did correlation of my data (2 categirical factors with 2 levels: Quantity & Quality; 2 dependent var: Irid.area & Casa.PC1, and 1 co-var: SL). But as some traits (here Irid.area) are significantly influenced by the covariate (standard length, SL), I
2014 Sep 01
1
Correlation Matrix with a Covariate
R Help - I'm trying to run a correlation matrix with a covariate of "age" and will at some point will also want to covary other variables concurrently. I'm using the "psych" package and have tried other methods such as writing a loop to extract semi-partial correlations, but it does not seem to be working. How can I accomplish this? library(psych) > set.cor(y =
2011 Oct 29
0
[LLVMdev] [llvm-commits] [PATCH] BasicBlock Autovectorization Pass
On Sat, 2011-10-29 at 15:16 -0500, Hal Finkel wrote: > On Sat, 2011-10-29 at 14:02 -0500, Hal Finkel wrote: > > On Sat, 2011-10-29 at 12:30 -0500, Hal Finkel wrote: > > > Ralf, et al., > > > > > > Attached is the latest version of my autovectorization patch. llvmdev > > > has been CC'd (as had been suggested to me); this e-mail contains > >
2011 Oct 29
4
[LLVMdev] [llvm-commits] [PATCH] BasicBlock Autovectorization Pass
On Sat, 2011-10-29 at 14:02 -0500, Hal Finkel wrote: > On Sat, 2011-10-29 at 12:30 -0500, Hal Finkel wrote: > > Ralf, et al., > > > > Attached is the latest version of my autovectorization patch. llvmdev > > has been CC'd (as had been suggested to me); this e-mail contains > > additional benchmark results. > > > > First, these are preliminary
2005 Apr 12
2
Perhaps Off-topic lme question
A question on lme() : details: nlme() in R 2.1.0 beta or 2.0.1 The data,y, consisted of 82 data value in 5 groups of sizes 3 9 8 28 34 . I fit a simple one level random effects model by: myfit <- lme( y~1, rand = ~1|Group) The REML estimates of between and within Group effects are .0032 and .53, respectively; the between group component is essentially zero as is clearly evident from a
2010 Jan 04
1
log-normal overlay
Hello, Using the following lines of code, I created the following graph:
2010 Jan 04
1
log normal overlay
Hello, Using the following lines of code, I created the following graph:
2011 Oct 29
0
[LLVMdev] [llvm-commits] [PATCH] BasicBlock Autovectorization Pass
On Sat, 2011-10-29 at 12:30 -0500, Hal Finkel wrote: > Ralf, et al., > > Attached is the latest version of my autovectorization patch. llvmdev > has been CC'd (as had been suggested to me); this e-mail contains > additional benchmark results. > > First, these are preliminary results because I did not do the things > necessary to make them real (explicitly quiet the
2011 Oct 29
4
[LLVMdev] [llvm-commits] [PATCH] BasicBlock Autovectorization Pass
Ralf, et al., Attached is the latest version of my autovectorization patch. llvmdev has been CC'd (as had been suggested to me); this e-mail contains additional benchmark results. First, these are preliminary results because I did not do the things necessary to make them real (explicitly quiet the machine, bind the processes to one cpu, etc.). But they should be good enough for discussion.
2012 Oct 17
3
aggregate function not working?
The aggregate function for some reason will now work for me. The error I'm getting is: "Error in sort.list(y) : 'x' must be atomic for 'sort.list' Have you called 'sort' on a list?" agPriceList=aggregate(PriceList$Size, list(PriceList$bandNum),sum) *Price list dataframe:* dput(PriceList) structure(list(Price = c(0, 8.18, 8.27, 10.42, 10.5, 10.6, 11.13,
2011 May 16
2
wireframe advice - with reproducible code
Dear List, i am trying to produce a 3d plot using wireframe using the code: wireframe(Residuals_FD ~ Elevation * Temperature, data = data2, scales = list(arrows = FALSE), drape = TRUE, colorkey = TRUE) As you can see when the code (using the data below) is run the plot area is set-up correctly but the actual surface is missing? Any help would be greatly appreciated. Chris #data Elevation
2016 May 25
1
Slow RAID Check/high %iowait during check after updgrade from CentOS 6.5 -> CentOS 7.2
On 2016-05-25 19:13, Kelly Lesperance wrote: > Hdparm didn?t get far: > > [root at r1k1 ~] # hdparm -tT /dev/sda > > /dev/sda: > Timing cached reads: Alarm clock > [root at r1k1 ~] # Hi Kelly, Try running 'iostat -xdmc 1'. Look for a single drive that has substantially greater await than ~10msec. If all the drives except one are taking 6-8msec, but one is very
2012 Jun 05
2
[LLVMdev] [PATCH] add x32 psABI support
If you are interesting to play around X32, you may refer to http://sourceware.org/glibc/wiki/x32 to bootstrap a local environment on Linux. Yours - Michael -----Original Message----- From: cfe-commits-bounces at cs.uiuc.edu [mailto:cfe-commits-bounces at cs.uiuc.edu] On Behalf Of Liao, Michael Sent: Monday, June 04, 2012 5:09 PM To: llvm-commits at cs.uiuc.edu; cfe-commits at cs.uiuc.edu
2013 Feb 15
2
data formatting
Dear Eliza, Try this: Lines1<-readLines(textConnection("1911.01.01?????? 7.87 1911.01.02?????? 9.26 1911.01.03?????? 8.06 1911.01.04?????? 8.13 1911.01.05????? 12.90 1911.02.06?????? 5.45 1911.02.07?????? 3.26 1911.03.08?????? 5.70 1911.03.09?????? 9.24 1911.04.10?????? 7.60 1911.05.11????? 14.82 1911.05.12????? 14.10 1911.06.13?????? 7.87 1911.06.14?????? 9.26
2017 Oct 05
0
RFM Analysis Help
Hi Hemant, As I suspected, the code broke when I got to the line: result <- rfm_auto(df, id="user_id", payment ="subtotal_amount", date="created_at") Error in rfm_auto(df, id = "user_id", payment = "subtotal_amount", date = "cr eated_at") : could not find function "rfm_auto" It looks like you are using the hoxo-m/easyRFM
2017 Oct 06
3
Help RFM analysis in R (i want a code where i can define my own breaks instead of system defined breaks used in auto_RFM package)
I'm trying to perform an RFM analysis on the attached dataset, I'm able to get the results using the auto_rfm function but i want to define my own breaks for RFM. as follow r <-c(30,60,90) f <-c(2,5,8) m <-c(10,20,30) but when i tried to define my own breaks i got the identical result for RFM i.e 111 for every ID. please help me with this with working R script so that i can get
2009 Sep 14
1
Best way to extract values from an aov object ?
I'm trying to write a function to automate doing a variance analysis, part of which involves doing some further calculations. The method I've been using isn't very robust, if variable names change then it stops working. For this dummy data > dput(assayvar,"") structure(list(Run = structure(c(1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 4L, 4L, 4L), .rk.invalid.fields =
2012 Jun 07
0
[LLVMdev] [PATCH] add x32 psABI support
Hi Folks, Anyone got chance to review the patch adding X32 psABI support? Yours - Michael -----Original Message----- From: llvm-commits-bounces at cs.uiuc.edu [mailto:llvm-commits-bounces at cs.uiuc.edu] On Behalf Of Liao, Michael Sent: Tuesday, June 05, 2012 11:18 AM To: llvm-commits at cs.uiuc.edu; cfe-commits at cs.uiuc.edu; llvmdev at cs.uiuc.edu; cfe-dev at cs.uiuc.edu Subject: Re:
2011 Jul 18
1
nls() and lines()
All - I'm having an issue with trying to plot a model derived from nls() onto a simple plot.? I have included a sample data set and the code that I've been using. ?? year month day?????? date location mileage? cost gallon????? cpg ? mpg????????? x 2009???? 1?? 4?? 1/4/2009????? BZN? 124585 19.39? 14.37 1.349339 10.71677 2009-01-04 2009???? 1? 15? 1/15/2009????? BZN? 124888? 23.2? 16.12
2009 Sep 09
1
Stats help with calculating between and within subject variance and confidence intervals
Hello. I'm trying to find a way in R to calculate between and within subject variances and confidence intervals for some analytical method development data. I've found a reference to a method in Burdick, R. K. & Graybill, F. A. 1992, Confidence Intervals on variance components, CRC Press. This example is for Balanced Data confidence interval calculation from Pg 62. The data are